As we approach 2026, Axis Group is helping enterprise Data & AI leaders modernize their analytics ecosystems—starting with the consumption layer. While platforms like Qlik, Tableau, Cognos, and MicroStrategy have delivered value for years, the rapidly evolving data landscape now favors unified and cloud-native ecosystems such as Microsoft Fabric, Databricks and Redshift. Many organizations naturally focus on licensing costs when evaluating change. However, the true cost of remaining on legacy BI platforms extends far beyond licensing—into missed opportunities, mounting technical debt, and the inability to leverage transformative AI capabilities. Taking a more holistic approach to modernization is no longer optional; it's essential for maintaining a competitive advantage in the Data & AI era.
The Market Has Spoken: A Seismic Shift in BI
The BI and analytics landscape has transformed more in the past two years than in the previous decade. Vendors like Amazon and Snowflake have expanded into analytics and visualization, while legacy players have attempted to diversify through acquisitions and incremental innovation. Meanwhile, Microsoft has surged ahead—integrating Power BI into its broader Data & AI ecosystem through Fabric. This isn’t simply a story of marketing momentum or feature parity. It’s about ecosystem viability—the ability to innovate, integrate, and attract talent at scale.
As legacy platforms lose market share, the ripple effects are increasingly visible:
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Declining vendor investment in innovation and slower response to market needs
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Reduced third-party support and fewer integration options as vendors focus customer attrition
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Shrinking talent pools as skilled Data & AI professionals focus on learning & upskilling on the platforms with better growth prospects
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Limited innovation cycles as R&D budgets shift to other priorities
With Microsoft once again leading on the Gartner Magic Quadrant for ABI Platforms, it's no coincidence—it’s validation of strategic execution. And for organizations planning out the right Data & AI trajectory, the journey begins with BI.
Behind the Scenes: The Real Opportunity Costs
1. Data Layer: The Hidden Lock-in
Legacy BI platforms often trap critical business logic inside proprietary data structures—QVDs in Qlik, Hyper extracts in Tableau, Framework Manager models in Cognos, or Intelligent Cubes in MicroStrategy.
Over time, your BI layer quietly accumulates and traps business logic and dependencies leading to hidden complexity and significant technical debt:
- Business rules buried in platform-specific scripting.
- Data lineage obscured by years of incremental changes.
- Integration challenges when connecting to modern AI and analytics tools.
The result? Your most valuable asset—your data—becomes less accessible and less reusable with every passing year. Liberation requires deliberate strategy and the right partner to assess & extract logic, modernize the architecture, and align to business purpose so that it is reusable across systems.
2. Licensing Costs: A Compounding Problem
In the past 2 years, a clear trend has emerged: vendors increasing pricing while extending contract terms. A 1-year, $100K contract can easily become a 3-year, $400K commitment—with no incremental value added.
A few other mechanisms can include:
- Forced bundling of unnecessary features to maintain core functionality
- User-based pricing models that penalize growth and broader data democratization
- Limited negotiating power as vendors assume migration costs are prohibitive
- Hidden infrastructure costs for on-premises deployments that continue to escalate
- Complex licensing tiers requiring expensive upgrades for basic functionality
In today's economic climate, FinOps leaders are scrutinizing every dollar. Continuing to invest in legacy BI platforms that don't underpin modernization is a poor use of budgets.
3. AI Integration: Falling Behind
While competitors leverage AI to accelerate decision-making, organizations on legacy platforms find themselves increasingly isolated from transformative capabilities. Many of these legacy BI systems truly struggle as they weren't architected for large language models, automated insights, or native integration with AI copilots—making it difficult to keep pace.
Modern platforms like Microsoft Fabric, by contrast, have AI capabilities woven in across the entire data lifecycle—from ingestion to visualization. Legacy systems that treat AI as a bolt-on will only widen the competitive gap.
This challenge is particularly pronounced for older platforms like Cognos and MicroStrategy, where AI features often feel bolted on rather than native to the platform architecture. For forward-thinking organizations, this represents an opportunity to rethink their "AI-readiness" strategy. We've seen significant success on the Microsoft Fabric front, particularly through the curated rollout of Copolit and its seamless integration across analytics workflows.
4. People: The Growing Talent Gap
Over the past few years, data & analytics talent has voted with its feet. Developers, engineers and architects are prioritizing certifications from platforms that offer growth, community, relevance and innovation. As a result:
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Skilled legacy BI professionals are aging out.
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Training pipelines for proprietary tools are shrinking.
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Remaining experts command premium rates.
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Knowledge silos grow as fewer people understand aging systems.
The cost of maintaining outdated skills is rising—both financially and operationally.
Microsoft Fabric: Where the Market is Heading
Microsoft Fabric represents the next evolution of enterprise analytics—a unified, AI-ready platform, with benefits that span well beyond visualization. Organizations making investments in Fabric have several advantages:
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Open and accessible data via SQL and open formats.
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Integrated AI with Copilot embedded throughout workflows.
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Massive talent ecosystem with growing expertise across industries.
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Unified governance and security across all data assets.
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Scalable, consumption-based pricing aligned to value delivered.
Axis Group recently partnered with a large North American manufacturer to establish their Fabric environment and migrate legacy BI workloads. By starting with the consumption layer, the organization drove rapid adoption, upskilled internal teams, and built executive momentum for broader Data & AI investment.
Taking Action: Your Path Forward
The question isn't whether to modernize—it's how quickly you can execute the transition while minimizing disruption. The right approach begins with understanding:
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How your business logic is trapped within legacy systems.
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The true total cost of ownership, including hidden operational expenses.
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Your AI readiness, both technically and organizationally.
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Accelerators for migration that can automate the process.
Preparing for Renewal
As your next renewal approaches, take this opportunity to evaluate your position. The market has already chosen its direction—and those who adapt first will lead.
Ready to take the first step? Axis Group’s BI strategists are ready to connect to help you and your team prepare a step-by-step migration path to a modern, AI-ready platform.
Axis Group has helped hundreds of organizations modernize their analytics platforms, reducing costs while accelerating innovation. With nearly 30 years of BI expertise across all major platforms, we understand the complexities of these systems and have developed revolutionary automation capabilities that can liberate your data and accelerate your journey to modern analytics.